ArticleNPJ systems biology and applications2026
Intelligent tool orchestration for rapid mechanistic model prototyping: MCP servers as AI-biology interfaces.
Article in NPJ systems biology and applications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Experimentally calibrated multiscale model predicts schedule dependent drug combination effects.NPJ systems biology and applications · 2026Article
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Authors and funding
3 authors.
Funding
Abstract
Constructing multicellular mechanistic models traditionally requires extensive time and computational expertise. We introduce intelligent tool orchestration via Model Context Protocol (MCP) servers, enabling Large Language Model (LLM) agents to act as AI laboratory assistants for rapid model prototyping. We demonstrate this approach by constructing a multiscale model of cancer cell fate in response to TNF using an AI agent connected to MCP servers interfacing with three complementary tools: NeKo for gene regulatory networks construction, MaBoSS for Boolean models simulation, and PhysiCell for setting up multicellular agent-based models. This workflow was executed entirely through natural language interactions, without manual coding, direct parameter editing, or manual modification of generated model files. Through this use case, we identified key principles for biological AI-tool integration, specifically regarding tool granularity, session management, and flexible orchestration. Testing across multiple LLMs demonstrated our framework's portability, though model-dependent variations emphasize the need for rigorous validation. Ultimately, this work establishes a foundation for AI-assisted rapid prototyping, enabling researchers to explore computational hypotheses more rapidly through natural language interaction.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.